K-Score Time Period – K-score and trend are calculated for three time periods : (1) Monthly – Last 30 days (2) Quarterly – Last 90 days (3) Yearly – Last 365 days. Depending upon the dynamics of your engagement with your opportunities and accounts you can choose any or all of them.

2. Basic K-Score Calculation

K-Score calculation can easily be customized to address specific needs beyond the basic calculation. The basic K-Score calculation is following this logic:

Meeting – highest score – meeting organizer gets 10 points

Meeting participant – 4 points

Email – sender gets 5 points

Email – recipients in the To line – 2 points

Email – recipients in the CC line – 1 points

For open loop email (the customer hasn’t replied) – the sender and every recipient get an additional 1 point.

For closed loop email (the customer has replied) – the sender and every recipient get an additional 7 points.

Email with attachment – gets a boost of extra 5 points

K-Score aggregates the number of points for each contact person, which is then rolled up to the opportunity and account level.

Decay logic

Activity done last month has lower impact on the engagement score versus activity that was done recently. To reflect it, the score is decayed along the time e.g. 1.5% every week.

K-Score normalization (0-100) logic

The raw calculated K-Score number is used to determine the 0-100 score based on % percentile with similar accounts, opportunities, etc. So if the raw value falls in the 73% percentile than K-Score will be 73.

It is also possible to compare K-Score vs similar type of accounts like Platinum or Gold accounts and not across all accounts. The same could be applied for opportunities.

3. K-Score Trend

K-Score trend is simply the delta between K-Score in the last period vs the last one. Thus, it can be positive or negative and between -100 to +100.

4. Usage

K-Score is added to each contact, account, opportunity and lead. It is posted into Salesforce and Dynamics native fields so you can leverage it in your reports and dashboard.

Furthermore, K-Score is one of the parameters that Komiko is used in its Machine Learning models to determine Account and Opportunity health score.